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Key Responsibilities
● Build and productionize data models for user segmentation, conversion, churn, and
monetisation
● Partner with Product to define success metrics, experimentation frameworks, and KPIs
● Drive A/B testing, funnel analysis, and cohort analysis to improve product outcomes
● Translate business problems into data-backed product insights and recommendations
● Work with large-scale transactional data across payments, rewards, and merchant flows
● Collaborate with Engineering to deploy models and analytics into live systems
● Create dashboards and narratives for leadership and external partners (issuers/merchants)
Requirements
● 4–6 years of experience as a Data Scientist in fintech, payments, or financial services
● Strong hands-on skills in Python, SQL, and statistical modeling
● Experience with product analytics, experimentation, and metrics design
● Solid understanding of transactional data, user behavior, and funnel optimization
● Ability to convert ambiguous business problems into structured data solutions
Job ID: 150933245
Skills:
Java, Node.js, Sql, Microservices, React, Gcp, Docker, Distributed Systems, Rest Apis, Azure, Kubernetes, Python, AWS, LLMs, GenAI APIs, NoSQL databases, modern JavaScript, CICD pipelines, vector stores, RAG architectures
Skills:
Data Science, Machine Learning, Advanced Analytics, Python, Sql, GenAI
Skills:
Machine Learning, SAS, Matlab, Python, Sql, R, Statistical Modeling, Data Analysis
Skills:
MLops, Sql, Python, GenAI, LLMs, ML frameworks
Skills:
containerization , agent coordination, Azure ecosystem, cloud-native GenAI solutions, agent-based workflows, LLM APIs, vector databases, CI CD, embedding generation, Python 3.11, model monitoring
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